Loading part from task B:
` def get_models_from_task(task: clearml.Task, model_artifact_substring: str = 'iter_') -> dict:
"""
Extract all models saved as artifacts with the specified substring

:param task: Task to fetch from
:param model_artifact_substring: Substring for recognizing models among artifacts
:return: Mapping between iter number and model instance
"""

# Extract models from task (models are named iter-XXX where XXX is the iteration number)
model_...

I double checked that the task object is the correct one

task here is a ClearML task object

For example, this is one execution:

I am noticing that the files are saved locally, is there any chance that the files are over-written during the run or get deleted at some point and then replaced?
Yes they are local - I don't think there is a possibility they are getting overwritten... But that depends on how clearml names them. I showed you the code that saves the artifacts, but this code runs multiple times from a given template with different values - essentially it creates like 10 times the same task with different param...

CostlyOstrich36

💪

I will

is this already available or only on github?

very cool

is it possible to access the children tasks of the pipeline from the pipeline object?

okay but still I want to take only a row of each artifact

Yep what 😄

got it

the ability to exexute without an agent i was just talking about thia functionality the other day in the community channel

I don't know, I'm the one asking the question 😄

I also ran it without $(pwd) on the Create Clearml task templates section, I added it because of CostlyOstrich36 's comments but it didn't help

hahaha

actually i was thinking about model that werent trained uaing clearml, like pretrained models etc

pgrep -af trains shows that there is nothing running with that name

Maybe the case is that after start / start_locally the reference to the pipeline task disappears somehow? O_O

Sorry I meant this link
https://azuremarketplace.microsoft.com/en-us/marketplace/apps/apps-4-rent.clearml-on-centos8

No I don't have trains anywhere in my code

Gotcha, didn't think of an external server as Service Containers are part of Github's offering, I'll consider that

sudo curl https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose.yml -o /opt/trains/docker-compose.yml

I don't have ifconfig

Let's take a step back. Let's remove the clearml-services from the docker compose for a second, and run it manually (then you can control everything). Once you have it running manually, let's try to replicate the setup back to the docker compose, make sense ?

I'd prefer not to docker-compose down as researchers are actively working on it, what do you say that I will manually kill the services agent and launch one myself?

Did not solve this

Continuing on this discussion... What is the relationship between configuring files_server and all the rest we just talked about and the the default_output_uri ?

👍